ATM regulates proteasome-dependent subnuclear localization of TRF1, which is important for telomere maintenance
Bibliographic record
Abstract
Ataxia telangiectasia mutated (ATM), a PI-3 kinase essential for maintaining genomic stability, has been shown to regulate TRF1, a negative mediator of telomerase-dependent telomere extension. However, little is known about ATM-mediated TRF1 phosphorylation site(s) in vivo. Here, we report that ATM phosphorylates S367 of TRF1 and that this phosphorylation renders TRF1 free of chromatin. We show that phosphorylated (pS367)TRF1 forms distinct non-telomeric subnuclear foci and that these foci occur predominantly in S and G2 phases, implying that their formation is cell cycle regulated. We show that phosphorylated (pS367)TRF1-containing foci are sensitive to proteasome inhibition. We find that a phosphomimic mutation of S367D abrogates TRF1 binding to telomeric DNA and renders TRF1 susceptible to protein degradation. In addition, we demonstrate that overexpressed TRF1-S367D accumulates in the subnuclear domains containing phosphorylated (pS367)TRF1 and that these subnuclear domains overlap with nuclear proteasome centers. Taken together, these results suggest that phosphorylated (pS367)TRF1-containing foci may represent nuclear sites for TRF1 proteolysis. Furthermore, we show that TRF1 carrying the S367D mutation is unable to inhibit telomerase-dependent telomere lengthening or to suppress the formation of telomere doublets and telomere loss in TRF1-depleted cells, suggesting that S367 phosphorylation by ATM is important for the regulation of telomere length and stability.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".